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Investigating the Three-dimensional Flow Separation Induced by a Model Vocal Fold Polyp
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Published on: February 3, 2014

Characterizing glottal jet turbulence.

Fariborz Alipour1, Ronald C Scherer

  • 1Department of Speech Pathology and Audiology, The University of Iowa, Iowa City, Iowa 52242, USA. alipour@blue.weeg.uiowa.edu

The Journal of the Acoustical Society of America
|March 9, 2006
PubMed
Summary
This summary is machine-generated.

Investigating airflow during voice production, this study compared methods for separating vocal fold turbulence from the main airflow signal. Smoothing emerged as the most effective technique for analyzing phonation velocities and turbulence.

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Area of Science:

  • Acoustic and Physiological Phonetics
  • Biomedical Engineering
  • Fluid Dynamics

Background:

  • Airflow from the lungs causes vocal fold oscillation, producing sound.
  • The glottal jet can exhibit both laminar flow and turbulence.
  • Understanding the glottal jet's turbulence is crucial for voice production analysis.

Purpose of the Study:

  • To investigate the separation of turbulence from the deterministic portion of the glottal jet.
  • To evaluate three methods for representing the deterministic signal and residual turbulence: smoothing, wavelet denoising, and ensemble averaging.
  • To determine the most appropriate method for analyzing phonation velocities in an excised canine larynx model.

Main Methods:

  • Utilized an excised canine larynx model to simulate voice production.
  • Applied three signal processing techniques: smoothing, wavelet denoising, and ensemble averaging.
  • Analyzed the ability of each method to represent both the deterministic glottal signal and the turbulent component.

Main Results:

  • Ensemble averaging exaggerated turbulence intensity while disregarding cyclic variations.
  • Wavelet denoising offered good analysis but faced challenges in selecting appropriate decomposition levels.
  • Smoothing effectively preserved cyclic variations crucial for voice modulation and extracted turbulence at reasonable levels.

Conclusions:

  • Smoothing is the most suitable method for analyzing phonation velocities and glottal jet turbulence.
  • This technique accurately represents voice perturbations and modulations while isolating turbulent airflow.
  • The findings provide a methodological advancement for studying voice production dynamics.